From Cognitive Radios over From Cognitive Radios over Millimeter Wave to Millimeter Wave to PicoRadiosPicoRadiosJan M. RabaeyScientific Co-Director BWRCEECS Dept.Univ. of California, Berkeley
Berkeley Wireless Research CenterBerkeley Wireless Research Center• A partnership of UC researchers, industry,
and government • Participating Members:
Agilent TechnologiesInfineon TechnologiesIntel CorporationSTMicroelectronicsHitachi LtdHewlett PackardSun Microelectronics
• Associate Members:Atmel CorporationCadenceEricsson Radio Systems SamsungNECQualcomm Incorporated
• Other Funding: DARPA, NSF, ONR, MARCO, MURI
• Operational since Feb.1999• Downtown Berkeley, 1 block from
campus• 11,000 sq. feet• 55 graduate students,
5 technical staff, 8 faculty
Overall budget: > 5 M$/year
The Center GoalsThe Center Goals• Pre-competitive research – beyond 5 years• In close collaboration with industrial partners• Focus on silicon (CMOS) implementation
– Explore novel and disruptive paradigms – Determine relationship between theoretical and
algorithmic advances and implementation– Understand tradeoffs between various implementation
architectures with respect to performance, power and cost
– Realize concept-proving prototypes using rapid design flow from algorithm to implementation
The BWRC Research AgendaThe BWRC Research AgendaDa
ta Ra
te
1Kb
10Kb
100Kb
1Mb
Cellular (WAN)
3G Cellular
2.5 G Cellular
802.11 (LAN)
802.1a
Bluetooth (PAN)
Sensor networks
Metropolitan
Zigbee (PAN)
More bit/secMore bit/secThe quest for spectral capacity• Improving spectral utilization: MIMO• Exploring new spectrum: 60 GHz• Overlaying spectrum: UWB• Re-cycling spectrum: Cognitive
The quest for spectral capacityThe quest for spectral capacity• Improving spectral utilization: MIMO• Exploring new spectrum: 60 GHz• Overlaying spectrum: UWB• Re-cycling spectrum: Cognitive
Ubiquitous embeddedwireless• Ultra-low cost• Ultra-low power • Small size
Ubiquitous embeddedUbiquitous embeddedwirelesswireless• Ultra-low cost• Ultra-low power • Small size
Cheaper bitsCheaper bits100Mb
10Mb
1m 10m 100m 1km 10km
Range
The Wireless ArenaThe Wireless Arena
Designing Radios to Improve Spectrum UtilizationDesigning Radios to Improve Spectrum UtilizationThe target: Ubiquitous wireless multimedia delivery
• Exploit spatial dimension• Improve utilization of spectrum
– UWB – use low transmit power– Cognitive – dynamically find spectra that
isn’t being used• Exploit new frequencies – 60 GHz
Exploiting Spatial Diversity Exploiting Spatial Diversity –– Multiple Antenna ArraysMultiple Antenna ArraysExample: 802.11n
Network Improve range
MAC
A B C A B C D
Minimize interference
TX RX
PHY
Increase data rateImprove reliabilityReduce multipath
But it’s costly …But it’s costly …H11
H41
Σ
H14
H44
Σ
TX RX
Demands intensive real-timematrix computations.
SVD22.6mm
19.3mm
E.g. a division-free, deflation-type and LMS-based SVD algorithm
Direct-mapped area estimates: > 200 mm2
Based on 1 V, 1 MHz, 16 bits and 0.25 µm CMOS technology.
How Many Antenna’s Do We Really Need?How Many Antenna’s Do We Really Need?A testbed for wireless experimentation• FPGA prototyping engines (4)• 2.4 GHz RF Front-ends (32)• Scalable multiple antenna transmission system
Combining Theory and ExperimentsCombining Theory and ExperimentsTotal Capacity for Time/Freq/Space [Poon03]:2 A Ω W T λ-2 log SNR
scatteringantenna area
Scattering angle measurements
Designing Radios to Improve Spectrum UtilizationDesigning Radios to Improve Spectrum Utilization
• Exploit spatial dimension• Improve utilization of spectrum
– UWB – use low transmit power– Cognitive – dynamically find spectra that isn’t
being used• Exploit new frequencies – 60 GHz
Window of OpportunityWindow of Opportunity
Time (min)
Freq
uenc
y (H
z)
Recent measurements by the FCC in the US show 70% of the allocated spectrum is not utilized
Time scale of the spectrum occupancy varies from msecs to hours
Existing spectrum policy forces spectrum to behave like a fragmented disk
Bandwidth is expensive and good frequencies are taken
Unlicensed bands – biggest innovations in spectrum efficiency
What is a Cognitive Radio?What is a Cognitive Radio?
Easement User
2nd-aryUser
2nd-aryUser
Licensee
Not-to-Interfere Basis
Below the Acceptable “Interference Temperature”
FCC diagram
Increase User spectrum efficiencies
• Cognitive radio requirements– co-exists with legacy wireless systems– uses their spectrum resources – does not interfere with them
• Cognitive radio properties– RF technology that "listens" to huge swaths of spectrum – Knowledge of primary users’ spectrum usage as a function of location and time– Rules of sharing the available resources (time, frequency, space)– Embedded intelligence to determine optimal transmission (bandwidth, latency, QoS)
based on primary users’ behavior
Cognitive RadiosCognitive RadiosC
onfig
urab
le a
rray RF
RF
RF
Sensor
Optimizer
ReconfigurableBaseband D
imen
sion
2
Feasibleregion
Constraints
• Sensor finds the feasible region• Optimizer selects the best waveform …
– when, how long, frequency, bandwidth, array configuration.• Reconfigurable baseband adapts to the optimal schemes.• Major challenges:
– Broadband RF– Intelligent flexible radios– Massive processing
Dimension 1
Designing Radios to Improve Spectrum UtilizationDesigning Radios to Improve Spectrum Utilization
• Exploit spatial dimension• Avoid interfering with primary users
– UWB – use low transmit power– Cognitive – dynamically find spectra that
isn’t being used• Exploit new frequencies – 60 GHz
6060--GHz Unlicensed AllocationGHz Unlicensed AllocationBandwidth and
channel properties suitable for ~1-Gbps
wireless link
If there is so much opportunity, why is there so little use of this band?
Power handling, linearity, and noise performance of circuits at 60 GHzTraditional mm-wave solutions are very expensive (InP, GaAs).System design challenges, baseband analog interface ……
CMOS is Capable of 60 GHz OperationCMOS is Capable of 60 GHz Operation
VGS = 0.65 V
VDS = 1.2 V
IDS = 30 mA
W/L = 80u/0.13u
C. H. Doan, S. Emami, A. M. Niknejad, and R. W. Brodersen, “Design of CMOS for 60GHz Applications,” in IEEE Int. Solid-State Circuits Conf. Dig. Tech. Papers, Feb. 2004.
mmmm--Wave Challenges: ModelingWave Challenges: Modeling
Measured and modeled IDS vs. VDS.
Conclusion:lumped transistor modelswork well into the 60 GHz range!
RF-LO coupler
Transmission-lineterminations
mmmm--Wave Challenges: DesignWave Challenges: Design
Dual-gate mixer
Single-gate mixer
60 GHz Wireless LAN System 60 GHz Wireless LAN System
10-100 m
• Objective: Enable a fully-integrated low-cost Gb/s data communication using 60 GHz band.
• Approach: Employ emerging, standard CMOS and SiGe technology for the radio building blocks. Exploit antenna array for improved gain and resilience.
Ubiquitous Embedded WirelessUbiquitous Embedded Wireless
Meso-scale low-cost wireless transceivers for ubiquitous wireless data acquisition that• are fully integrated
–Size smaller than 1 cm3
• minimize power/energy dissipation– Limiting power dissipation to 100 µW
enables energy scavenging
• support low data-rates (< 100 kBit/sec)• and form self-configuring, robust, ad-hoc networks containing 100’s to 1000’s of nodes
Meso-scale low-cost wireless transceivers for ubiquitous wireless data acquisition that• are fully integrated
–Size smaller than 1 cm3
• minimize power/energy dissipation– Limiting power dissipation to 100 µW
enables energy scavenging
• support low data-rates (< 100 kBit/sec)• and form self-configuring, robust, ad-hoc networks containing 100’s to 1000’s of nodes
Berkeley PicoRadio ProjectBerkeley PicoRadio Project
“Ambient Intelligence” (The Concept)“Ambient Intelligence” (The Concept)• An environment where technology is embedded, hidden in the
background • An environment that is sensitive, adaptive, and responsive to
the presence of people and object• An environment that augments activities through smart non-
explicit assistance• An environment that preserves security, privacy and
trustworthiness while utilizing information when needed and appropriate
Fred Boekhorst, Philips, ISSCC02
The road to lowThe road to low--energy, lowenergy, low--cost, smallcost, small--sizesizeNot wireless as usual!Not wireless as usual!• Simplicity rules!
– Advanced techniques used in traditional wireless links are not necessarily relevant
– Looking back at the techniques of old• Standby power the greatest enemy
– Monitoring connectivity dominates overall power– Leakage dominates digital power
• Redundancy and randomness as a means to create robustness – Elements and links can and will fail– The environment and its conditions change rapidly
LowLow--Power RF: Back to The FuturePower RF: Back to The Future(Courtesy of Brian Otis)(Courtesy of Brian Otis)
© 1949 - superregenerativefc= 500MHz2 active deviceshigh quality off-chip passives - hand tuning D. Yee, UCB
© 2000 - Direct Conversionfc= 2GHz>10000 active devicesno off-chip components
RFRF--MEMS: The OpportunityMEMS: The Opportunity
Thin-Film Bulk Acoustic Resonator (FBAR [Ruby,ISSCC01])Q > 1000 @ 2 GHz
RadialBulk Acoustic Resonator (RBAR)Q > 500; f > 1 GHz
CMOS Metallization Stack
ri rog
Sense Electrode
Drive Electrode
Passive micro-resonators• High Q (> 1000)• High Frequency (> 1 GHz)• Very Small• Potential for integration
OSC1
OSC2
Back to the FutureBack to the Future
MatchingNetwork
MOD1
MOD2
Preamp PA
RF Filter A
fclockRF Filter Env
Det ∫
fclockRF Filter Env
Det ∫
Receiver
RF Amp Test
LNATest
Diff Osc
PA Test
TX1
TX2Env DetTest
Passive Test Structures
4 mm
• Minimizes use of active components –exploits new technologies such as RF-MEMS
• Uses the simple modulation scheme (OOK)• Allows efficient non-linear PA• Down-conversion through non-linearity (Diode)• Tx and Rx in 1-2 mW range (when on)
FBARFBAR--basedbased
Thin-Film Bulk Acoustic Resonator
The Return of The Return of SuperregenerativeSuperregenerative1500µm
1200
µm
• Fully Integrated Receiver Front-end
• 400µA when active(~200µW) with 50% quench duty cycle
RF In
Osc Out
BB Out
(Currently in fab -prototype expected early January)
A
fclockRF Filter Env
Det ∫
fclockRF Filter Env
Det ∫
Dealing with Standby Power:Dealing with Standby Power:The Reactive or WakeThe Reactive or Wake--Up RadioUp Radio
Information Burst
-
LCARF Filter
RF FilterDetector
Wake-up Radio:Low Gain, Low Sensitivity, Low BER
Wake-up Signal
RF Filter
Shifts Burden to TransmitterReduces monitoring power to < 50 µW
Realizing subRealizing sub--100 100 µµW carrierW carrier--sensesensePrototyping building blocks
-100dBc/Hz@1MHz offset
Phase noise
150mV(Vdd=500mV)
Differential output swing
1.5GHzOscillation frequency
150µACurrent consumption
0.5 – 1.2VSupply voltage
Another example: 140 µW 26 MHz wake-up receiver(R. Banna, N. Weste, UNSW)
Example: sub-threshold RF oscillatorusing integrated LCs (in fab)
Simulated Performance
Wireless Sensor Network Protocol ProcessorWireless Sensor Network Protocol Processor
In fab (Jan 04)
µWsStandby Power
< 1 mWOn_Power
3mm x 2.75mm =8.2 mm2
Chip Size
0.13µ CMOSTechnology
1V(High) –0.3V(Low)Core Supply Voltages
68KbytesOn Chip memory
16MHz(Main), 1MHz(BB)
Clocks Freqs
62.5K gatesGate Count
3.2MTransistor Count
64Kmemory DW8051
µc
BaseBand
SerialInterface
GPIOInterface
LocationingEngine
Neighbor List
SystemSupervisor
DLL
NetworkQueues
VoltageConv
Integrates all digital protocol and applications functions ofwireless sensor nodeMain Features:
- As simple as can be- Aggressive power management
EnergyEnergy--Scavenging becoming a RealityScavenging becoming a Reality• A self contained 1.9GHz transmitter - powered by Solar & Vibrational energy only
Light Level Duty CycleLow Indoor Light 0.36%
Fluorescent Indoor Light 0.53%Partly Cloudy Outdoor Light 5.6%
Bright Indoor Lamp 11%High Light Conditions 100%
Vibration Level Duty Cycle2.2m/s2 1.6%5.7m/s2 2.6%
Front
FBAR
TXBack
10 µFcap
Extrapolating towards the futureExtrapolating towards the future• How far can we push cost, size, and power? Can
we make “real” smart dust?• Absolutely! By going completely non-traditional!
– Ultra-dense networks: get the nodes closer, use lots of them, and make their energy consumption absolutely minimal (this is < 10 µW).
– Use non-tuned mostly passive radio’s – center carrier frequency randomly distributed
– Use statistical distribution to ensure reliable data propagation
• Leads to “smart surfaces”: sensitive plane wings, adaptive fabrics, intelligent walls
The Roadmap to UltraThe Roadmap to Ultra--dense Networksdense Networks
NEMS?
Super-regenerative:< 500 µW
Resonant bodyFinfet
Untuned mostlypassive< 5 µW
Untuned Subthreshold< 50 µW
Powering UltraPowering Ultra--Dense NetworksDense Networks
Anchor Spring flexure Comb fingers
Energy generation and conversion network
Energy Source 1
Energy Source 2
ConversionNetwork 1
ConversionNetwork 2
Reservoir 1(capacitor)
Reservoir 2(microbattery)
Needs integrated meso-scale energy train
Micro-battery
Electrostatic MEMSvibration converters
Summary and PerspectivesSummary and Perspectives• Wireless a key enabler to realization of truly
ubiquitous and disappearing electronics• Opening the door for amazing new
applications– Sensor networks, ambient intelligence, home
gateways, …• Making these come true requires new
paradigms, novel architectures, aggressive and alternative technologies, and tight integration of all components
• The change is truly “in the air”